{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "迁移学习教程\n",
    "========================== \n",
    "\n",
    "在这个教程里，我们会学习怎么使用迁移学习来训练模型。通常我们的训练数据量不会很大，很难达到像ImageNet那样上百万的标注\n",
    "数据集。我们可以使用迁移学习来解决训练数据不足的问题。\n",
    "\n",
    "迁移学习里，我们根据训练数据的多少通常可以采取如下方法：\n",
    "\n",
    "- 如果训练数据很少，那么我们通常把一个pretraning的网络的大部分固定住，然后只是把最后一个全连接层换成新的(最后一层通常是不一样的，因为分类的数量不同)，然后只训练这一层\n",
    "\n",
    "- 如果训练数据稍多一些，那么我们可以把pretraining的网络的前面一些层固定住，但后面的层不固定，把最后一层换新的，然后训练\n",
    "\n",
    "- 如果训练数据更多一些，那么所有的pretraining的层都可以fine-tuning，只是用pretraining的参数作为初始化参数。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# License: BSD\n",
    "# Author: Sasank Chilamkurthy\n",
    "\n",
    "from __future__ import print_function, division\n",
    "\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.optim as optim\n",
    "from torch.optim import lr_scheduler\n",
    "import numpy as np\n",
    "import torchvision\n",
    "from torchvision import datasets, models, transforms\n",
    "import matplotlib.pyplot as plt\n",
    "import time\n",
    "import os\n",
    "import copy\n",
    "\n",
    "plt.ion()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "加载数据\n",
    "---------\n",
    "\n",
    "我们使用torchvision和torch.utils.data包来加载数据\n",
    "\n",
    "\n",
    "我们要解决的问题是训练一个模型来区分**蚂蚁** and **蜜蜂**。每个类别我们大概有120个训练数据。\n",
    "另外每个类有75个验证数据。这是一个很小的训练集，如果直接用一个神经网络来训练，效果会很差。现在我们用迁移\n",
    "学习来解决这个问题。数据可以在[这里](https://download.pytorch.org/tutorial/hymenoptera_data.zip)下载。也可以在[这里](https://media.githubusercontent.com/media/fancyerii/fancyerii.github.io/master/assets/hymenoptera_data.zip)下载。\n",
    "下载后请解压到data目录下。\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 训练的时候会做数据增强和归一化\n",
    "# 而验证的时候只做归一化\n",
    "data_transforms = {\n",
    "    'train': transforms.Compose([\n",
    "        transforms.RandomResizedCrop(224),\n",
    "        transforms.RandomHorizontalFlip(),\n",
    "        transforms.ToTensor(),\n",
    "        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
    "    ]),\n",
    "    'val': transforms.Compose([\n",
    "        transforms.Resize(256),\n",
    "        transforms.CenterCrop(224),\n",
    "        transforms.ToTensor(),\n",
    "        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
    "    ]),\n",
    "}\n",
    "\n",
    "data_dir = '../data/hymenoptera_data'\n",
    "image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x),\n",
    "                                          data_transforms[x])\n",
    "                  for x in ['train', 'val']}\n",
    "dataloaders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=4,\n",
    "                                             shuffle=True, num_workers=4)\n",
    "              for x in ['train', 'val']}\n",
    "dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'val']}\n",
    "class_names = image_datasets['train'].classes\n",
    "\n",
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "可视化图片\n",
    "\n",
    "^^^^^^^^^^^^^^^^^^^^^^\n",
    "我们来显示几张图片看看。\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def imshow(inp, title=None):\n",
    "    inp = inp.numpy().transpose((1, 2, 0))\n",
    "    mean = np.array([0.485, 0.456, 0.406])\n",
    "    std = np.array([0.229, 0.224, 0.225])\n",
    "    inp = std * inp + mean\n",
    "    inp = np.clip(inp, 0, 1)\n",
    "    plt.imshow(inp)\n",
    "    if title is not None:\n",
    "        plt.title(title)\n",
    "    plt.pause(0.001)  \n",
    "\n",
    "\n",
    "# 得到一个batch的数据\n",
    "inputs, classes = next(iter(dataloaders['train']))\n",
    "\n",
    "# 把batch张图片拼接成一个大图\n",
    "out = torchvision.utils.make_grid(inputs)\n",
    "\n",
    "imshow(out, title=[class_names[x] for x in classes])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "训练模型\n",
    "------------------\n",
    "\n",
    "现在我们来实现一个用于训练模型的通用函数。这里我们会展示：\n",
    "\n",
    "-  learning rate的自适应\n",
    "-  保存最好的模型\n",
    "\n",
    "在下面的函数中，参数``scheduler``是来自``torch.optim.lr_scheduler``的LR scheduler对象(_LRScheduler的子类）\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_model(model, criterion, optimizer, scheduler, num_epochs=25):\n",
    "    since = time.time()\n",
    "\n",
    "    best_model_wts = copy.deepcopy(model.state_dict())\n",
    "    best_acc = 0.0\n",
    "\n",
    "    for epoch in range(num_epochs):\n",
    "        print('Epoch {}/{}'.format(epoch, num_epochs - 1))\n",
    "        print('-' * 10)\n",
    "\n",
    "        # 每个epoch都分为训练和验证阶段\n",
    "        for phase in ['train', 'val']:\n",
    "            if phase == 'train':\n",
    "                scheduler.step()\n",
    "                model.train()  # 训练阶段\n",
    "            else:\n",
    "                model.eval()   # 验证阶段\n",
    "\n",
    "            running_loss = 0.0\n",
    "            running_corrects = 0\n",
    "\n",
    "            # 变量数据集\n",
    "            for inputs, labels in dataloaders[phase]:\n",
    "                inputs = inputs.to(device)\n",
    "                labels = labels.to(device)\n",
    "\n",
    "                # 参数梯度清空\n",
    "                optimizer.zero_grad()\n",
    "\n",
    "                # forward\n",
    "                # 只有训练的时候track用于梯度计算的历史信息。\n",
    "                with torch.set_grad_enabled(phase == 'train'):\n",
    "                    outputs = model(inputs)\n",
    "                    _, preds = torch.max(outputs, 1)\n",
    "                    loss = criterion(outputs, labels)\n",
    "\n",
    "                    # 如果是训练，那么需要backward和更新参数 \n",
    "                    if phase == 'train':\n",
    "                        loss.backward()\n",
    "                        optimizer.step()\n",
    "\n",
    "                # 统计\n",
    "                running_loss += loss.item() * inputs.size(0)\n",
    "                running_corrects += torch.sum(preds == labels.data)\n",
    "\n",
    "            epoch_loss = running_loss / dataset_sizes[phase]\n",
    "            epoch_acc = running_corrects.double() / dataset_sizes[phase]\n",
    "\n",
    "            print('{} Loss: {:.4f} Acc: {:.4f}'.format(\n",
    "                phase, epoch_loss, epoch_acc))\n",
    "\n",
    "            # 保存验证集上的最佳模型\n",
    "            if phase == 'val' and epoch_acc > best_acc:\n",
    "                best_acc = epoch_acc\n",
    "                best_model_wts = copy.deepcopy(model.state_dict())\n",
    "\n",
    "        print()\n",
    "\n",
    "    time_elapsed = time.time() - since\n",
    "    print('Training complete in {:.0f}m {:.0f}s'.format(\n",
    "        time_elapsed // 60, time_elapsed % 60))\n",
    "    print('Best val Acc: {:4f}'.format(best_acc))\n",
    "\n",
    "    # 加载最优模型\n",
    "    model.load_state_dict(best_model_wts)\n",
    "    return model"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "可视化模型的预测结果\n",
    "\n",
    "^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def visualize_model(model, num_images=6):\n",
    "    was_training = model.training\n",
    "    model.eval()\n",
    "    images_so_far = 0\n",
    "    fig = plt.figure()\n",
    "\n",
    "    with torch.no_grad():\n",
    "        for i, (inputs, labels) in enumerate(dataloaders['val']):\n",
    "            inputs = inputs.to(device)\n",
    "            labels = labels.to(device)\n",
    "\n",
    "            outputs = model(inputs)\n",
    "            _, preds = torch.max(outputs, 1)\n",
    "\n",
    "            for j in range(inputs.size()[0]):\n",
    "                images_so_far += 1\n",
    "                ax = plt.subplot(num_images//2, 2, images_so_far)\n",
    "                ax.axis('off')\n",
    "                ax.set_title('predicted: {}'.format(class_names[preds[j]]))\n",
    "                imshow(inputs.cpu().data[j])\n",
    "\n",
    "                if images_so_far == num_images:\n",
    "                    model.train(mode=was_training)\n",
    "                    return\n",
    "        model.train(mode=was_training)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finetuning模型\n",
    "----------------------\n",
    "\n",
    "加载一个预训练的模型，重置最后的全连接层，然后重新训练模型。\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_ft = models.resnet18(pretrained=True)\n",
    "num_ftrs = model_ft.fc.in_features\n",
    "model_ft.fc = nn.Linear(num_ftrs, 2)\n",
    "\n",
    "model_ft = model_ft.to(device)\n",
    "\n",
    "criterion = nn.CrossEntropyLoss()\n",
    "\n",
    "# 所有的参数都可以训练\n",
    "optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\n",
    "\n",
    "# 每7个epoch learning rate变为原来的10% \n",
    "exp_lr_scheduler = lr_scheduler.StepLR(optimizer_ft, step_size=7, gamma=0.1)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "训练和评估\n",
    "\n",
    "^^^^^^^^^^^^^^^^^^\n",
    "\n",
    "在CPU上通常需要15-25分钟，而GPU上不到一分钟就可以训练完成\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0/24\n",
      "----------\n",
      "train Loss: 0.6778 Acc: 0.6598\n",
      "val Loss: 0.2497 Acc: 0.9150\n",
      "\n",
      "Epoch 1/24\n",
      "----------\n",
      "train Loss: 0.6869 Acc: 0.7295\n",
      "val Loss: 0.6803 Acc: 0.8105\n",
      "\n",
      "Epoch 2/24\n",
      "----------\n",
      "train Loss: 0.6460 Acc: 0.7623\n",
      "val Loss: 0.3178 Acc: 0.8627\n",
      "\n",
      "Epoch 3/24\n",
      "----------\n",
      "train Loss: 0.6041 Acc: 0.7213\n",
      "val Loss: 0.4568 Acc: 0.8105\n",
      "\n",
      "Epoch 4/24\n",
      "----------\n",
      "train Loss: 0.4706 Acc: 0.8074\n",
      "val Loss: 0.4201 Acc: 0.8693\n",
      "\n",
      "Epoch 5/24\n",
      "----------\n",
      "train Loss: 0.4898 Acc: 0.8197\n",
      "val Loss: 0.3838 Acc: 0.8497\n",
      "\n",
      "Epoch 6/24\n",
      "----------\n",
      "train Loss: 0.4372 Acc: 0.8156\n",
      "val Loss: 0.4540 Acc: 0.8562\n",
      "\n",
      "Epoch 7/24\n",
      "----------\n",
      "train Loss: 0.2777 Acc: 0.8770\n",
      "val Loss: 0.3085 Acc: 0.8954\n",
      "\n",
      "Epoch 8/24\n",
      "----------\n",
      "train Loss: 0.2322 Acc: 0.9057\n",
      "val Loss: 0.2815 Acc: 0.9020\n",
      "\n",
      "Epoch 9/24\n",
      "----------\n",
      "train Loss: 0.4153 Acc: 0.8156\n",
      "val Loss: 0.3059 Acc: 0.8824\n",
      "\n",
      "Epoch 10/24\n",
      "----------\n",
      "train Loss: 0.2533 Acc: 0.9016\n",
      "val Loss: 0.2875 Acc: 0.9020\n",
      "\n",
      "Epoch 11/24\n",
      "----------\n",
      "train Loss: 0.2689 Acc: 0.8975\n",
      "val Loss: 0.2895 Acc: 0.8954\n",
      "\n",
      "Epoch 12/24\n",
      "----------\n",
      "train Loss: 0.3179 Acc: 0.8730\n",
      "val Loss: 0.2623 Acc: 0.9085\n",
      "\n",
      "Epoch 13/24\n",
      "----------\n",
      "train Loss: 0.3045 Acc: 0.8730\n",
      "val Loss: 0.2445 Acc: 0.8954\n",
      "\n",
      "Epoch 14/24\n",
      "----------\n",
      "train Loss: 0.2992 Acc: 0.8934\n",
      "val Loss: 0.2836 Acc: 0.9150\n",
      "\n",
      "Epoch 15/24\n",
      "----------\n",
      "train Loss: 0.2857 Acc: 0.8811\n",
      "val Loss: 0.2549 Acc: 0.9085\n",
      "\n",
      "Epoch 16/24\n",
      "----------\n",
      "train Loss: 0.3053 Acc: 0.8730\n",
      "val Loss: 0.2534 Acc: 0.9150\n",
      "\n",
      "Epoch 17/24\n",
      "----------\n",
      "train Loss: 0.2677 Acc: 0.8975\n",
      "val Loss: 0.2732 Acc: 0.9020\n",
      "\n",
      "Epoch 18/24\n",
      "----------\n",
      "train Loss: 0.3114 Acc: 0.8770\n",
      "val Loss: 0.2584 Acc: 0.9020\n",
      "\n",
      "Epoch 19/24\n",
      "----------\n",
      "train Loss: 0.2859 Acc: 0.8770\n",
      "val Loss: 0.2569 Acc: 0.9020\n",
      "\n",
      "Epoch 20/24\n",
      "----------\n",
      "train Loss: 0.3350 Acc: 0.8566\n",
      "val Loss: 0.2505 Acc: 0.9020\n",
      "\n",
      "Epoch 21/24\n",
      "----------\n",
      "train Loss: 0.2756 Acc: 0.8934\n",
      "val Loss: 0.2458 Acc: 0.9020\n",
      "\n",
      "Epoch 22/24\n",
      "----------\n",
      "train Loss: 0.2630 Acc: 0.8893\n",
      "val Loss: 0.2522 Acc: 0.9085\n",
      "\n",
      "Epoch 23/24\n",
      "----------\n",
      "train Loss: 0.2487 Acc: 0.9057\n",
      "val Loss: 0.2760 Acc: 0.9150\n",
      "\n",
      "Epoch 24/24\n",
      "----------\n",
      "train Loss: 0.2229 Acc: 0.9057\n",
      "val Loss: 0.2602 Acc: 0.9020\n",
      "\n",
      "Training complete in 1m 26s\n",
      "Best val Acc: 0.915033\n"
     ]
    }
   ],
   "source": [
    "model_ft = train_model(model_ft, criterion, optimizer_ft, exp_lr_scheduler,\n",
    "                       num_epochs=25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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dElWlUidnZ5GNpsnUMTGKEe+UYRwwXjM23ZA+N/zSvTn1cMyWwvW9GZM6kkcjlAQyOvLyPBai7hzs8sLVjjdnSwKGj4bc2m/Z2T7g3OaERyc7VMsZt7sB68MhX712j0WInB4a65Mxy5DZF2N/Z8GN3V2mwyFfePE1Tq0OkTjkzZ0ZaM0gJB7dGLMxXuOla/dYmw4Qj0yi0nrghWu3OLe2zum6Yrq+wvPXbvB9jz1MpZBd3nr0xRiQfI/gSmuGNFCRqYLiXmLmoUcYGMsucGE0oh5WdAhrwxGz7CyyMwyR6fCEztLsLjNtmrN1ZpPxsuX/e/lNWndGkwnXdxZcv/cmP/Opp9neb3ntIHNxbcCsmfPmEv7Z5W3awZgvPHeVp86OeOTSOd68scNnX57xvU+O2N6+yaObU86crXnl5j7tYMrlF17mI+97iJevzOnaOdPJmHMbkXt7C27vZ546f4r10PErn3uDD57ZYHNlBY0VN2ZLHppWkJ3X7i2ZDoacHUWSOEHLHCxWMlWugjnEWNHVDubc2p/TEjg3qiAEOluS34MnH47FmHp+ZZXbTeaffukV/vfnXsVXH2JcB+azli4HRrHm7//ey/z2aze5cesuIpE4nPBPXr7HlabmjVs7fPTJh9lcGfL1F6+ye2vBNMDezpxz62Mk1ux0kY2tM1zdXbLMNV94+TqZBfe6TDUe8Rsv3ORGO2FH4B/9/ku8dLcj4nz9ym1uNw3byVCUG7tLsDkbgyHzxYIuw97ScFr2M7QKjSm7Xce1WeLazh5IxwGZnc64vr0NwRkNI1qPsHe1nPbbs2Mh6iDCxx9aQdOClUnNYP8m3aLlzEMrhNziCnVUdKhUMXPHG27f2+PPnKsZ7t5jDWOvTTx/t+XVuwfMlh0/9NFLPHRmyuBey2ow7l6+yUtvXOfK9dss2gWXt5fsD8+xv9fy2d+/TKU13XKHg71ddjvltfmSJz/0BF++t2Tl0bNcOVjy4q2bnFmZMssAwsZoyCzD9b0lO60T1REZgNR4m6iScXW3ZWchaILTw5qHN8+QMly+M+P27g77i6Nvqsei+/3iy9f4+DMXOL8+5f1nJxzohHND5+7dPc5cPMXd/X3GozFpmWimY2a35yws0WZYeMsbVxdM1lqee2PGj3zfEzR7t+nmO2xNJ3x50WCvtoxGFc9d3meggYHAzDJ7X3iepkk8cWGds2en3LqzQIeBh8+d5ubtbaJ27C8Sv/k7X+XPfewp/OmLfO3FK9zcWfLYMPDm/i4bWnGuCozEaS0zJFPHGh0ow6rm3HLBN3YP+NjmiI0q4kGoq8hIlf3GWb4HszTHoqX+9J//V5jtHTBZGdNJxRNbI/aScebUKuPJEB3WvHptRiCw2F5yR2vGwxFX9ha8cD1z7uwmm6MRW8PAb/3uq7x8Zc76+XM8d/kOT3/3RbY7Y7/JbA4DS3NayRhwa9HyvvUxebnP7vaCMzUwW7CzcxfESK585tPPsr2X+cX/+f/lV/7v32NjZDz58Drd2pQf+fGfZG0SOL+5xjDWqBmzvODOfM7MK5I6506t8ezpCaoVHZmGli6V3PXp8YBzo6N3lI7FAqmf+6En/IkzQy63ke9aGbLbHvC7r9yBesDWOGDLzBdvzFhdXWF3d8bmhfNs2D63zTk9HPDKtbs0+wsuPH6Ba2/u0OWWyzcXfOZTH+CNN64zGQdSZ9zYWXBlN1PnxMKVhRk//NHHuXtvm92dBYrRtokuZabDmq3Nmq3zW+S9xKe//ym+/twL7LbKhVNjbu3sgy95/P1PMcH5wEoFKZPrwHJ/zs5+g+WOySgQRfiNV3YZsuSDj2yyUilJhsQu8c2du/z0//nKkWb1j4Wo/9df+6TXQdlbHvDZr13l09/9MF95Y4920bDbNjy6NmJcj3jhYEGzu2DvIDMeCKrOQ4+epTLY3d1jczzi4GCPO92Ie+bcunyD3QY+8MiUO3tLbh8kPv3kFuMotMm5d7CkBb7y5oxPPLnFXmu8+M27QGZBYJ4zP/H0Ord3E6uTwOrKCh86t8EgO7/7+jXyQBhnpWOBhxFXbu/y1z/9Yc5PRmTLZGsIHjDNaHZmiwXDQQ06IFhmppEvvn6V/+TXXz15yy4m45oqGzoaUU9Wub2zZG+W+d73n8GCkVojOoThiJWLwjeuztjb2WN/EIg7e4zWxpx/5CJrQ2dFttiRIQfXbvDm9Ayv3JgzBP6DH/8YrSV+7le/TDWs+e5HNlgbT5lqvy5GYOTOubWaN3cWDHFGtfLiGwf82U99lG984SusDCNuG2ysDfhL3/MEv/yV2zzxkHN6cp7f/uYVJiL82teuMEgL/q0//0nCfIeDtkFMiOMtBvkO2TOeWlwCY+v45IX1Iy/PY9FSf+c/+lFPOUGs6fZn/NYbt9jdXfJDT5xlPwXqKrBZCwfNghtzWBvC51/f4Znz62xubfLq9TfZsJonzmyQKiVoJFvm7t6Sz7/0Oq1U5MWCH/zYd/GNVy7TLTNv3NuDWnnh6gEbG1MurSpfubLHMw9t8PXLt9hOZfmGxsBj57e4tAJ3D1oGdc3pYeTHv+thYhxSR+jcCSYsLJNzw62dhsvzDg1zPvbYJaTZo5KAe0XQgHX7uBkWKzp3PvV3PnfyWmocTKmsI6iyN+r48Lkpz+uQuSnLLnNmXHG3zXzk48+w/fkXWFlb4RPnWjzWfPW5V5ktl4wfPUsbnGkUUhVJ+y2nRpFPP/M+rKrYRzlVKetrU848VPE9H3qY51+/xbPPXOLLb97jJ594iNA9D2ROjSrOasVMMvtNZty2XLmz4CPnN9nRAZfWhmSgaw8YVGOGdY1HmHRD9hvh4gacXRvx6r3Ift1x7uIH2X75edLqCtOdO4SoiAeWJvz6l1/jU0ddnkd8vj+S2XKPtc0p+7fn3N7d48svz/m+j1xg4sBygaoyGir/5De+wdI74tlVts4OeO7aLdrxiPMrFd1sj29a4sPvO0fVLokqvHTjLue31lFz1nRBHVb5wJk1vEs0jdF0xlkyH33sDDasqc9f4OObK/zrm2P2Fw2v3bjLl167wccePcf1nXtcWSSefWSVl+4e8PDpKdPpOrEy8I62E8gNkzrQhRHazNlYG/Ly125x+ev3uPSRR7jy6h129+9xqo48vbnGOBg/+aFL/9Ly+XbtWIQ0IUR27xzQqrJZRU5PhTeu3eHLl7cJG6eoBzWLnT225wseX19hdb7HNCaq+T5PryqXtjb5yFMX2d9bcHN7hscKqsD5zRX+l8+9TFUFpiurHDQLJoOacQVv7O6z7BLWNHzlhVeoVfHZPV66s82iMUZReGhrk48/dpaNtYqttRUeHg343Cv3+Iknz/HmnV02KqHNRg4TtJrQOVy7u01MHbMUGA6H1NoRKmP/pde4cuUyZ4YTRAL7qUOoyaE68vI8Fi21XSyp11fhYMndLnJxfcCtNrNWVXjbEjwxGa/gd64xGg8ZkNEQ+cRTj9AmY3d/jqbIpfOnuLGzZKVShrFiZX2DH/6ep2ljjabE1uaE7f3EzAOShYfXA51AzoGDruEHLj3KfnPAVy9fI1QBa5Y8c3ETb+Gl2ZyPPfEIP1BX/L2vvc7PPPskXS4OnKUDOg9Q1yxb+Mcv3+WTTzzE7e09rDNODZ0Lm+ucPXee7WXDqJ0zFPDcUcsJzSi9eHNGuDvjofUxZ0bCcrzBalUTlwfkqkKmE56/c5uLZza4urPPxVOrVMMJaXaXqq44u7FKC6yu1uzu3mayeZaajoPGeN8koAPBDoyvvnqTh05NySi3d+9x4cwaajWfeGwL7RJxGKgs8NS5FW7MO3QUEEmsbpziWcmsr4xxhL/y4ce5s1hwZjrCdVBWBDSJajhkXEVOT4TU7BMUujDAXbhya4+LpxZseUBGSuoSg0lk/+CEPsy9MztgpVJW65pxrUxRJpYYxop4sCTvzPjARIhUPLoxJYynzHKLWURWT0ElmBtTMZ48v4kuZ+QuUdsBlTq+aKBShoOa3/nGVdqDA/7cBy5yYTrlsYsbPLM1QYPx+r0Dru0csDKe8r71IZYCL765yyDNWV1bo6JjIB2TAZwbj/FssNzHU6IajtF5y9n1CX/m0XOMhyPqQc1a5YRpzWg85iArKUSWraOiXNmZ88rd3SMvz2PRUi+dHrGjNWtdZmU0QkPCcoXnJfV0TPDEeKhsTMpD2TJfUkchB/Blw94cBpXQZaMa1zSiDFUQr8AzMVakKJwdRrYunWW7a5jLgOFaIDULpBoxnEbG924yXl+nGgi3Z/D7r93kM8++D9Uh00lNF8bYcp/OM6F/PlzCAHPFXKhXVwj3WtQzQQNbY7jw+HmalJCgVBJZzBfM2yVf3A/cvbvNe0AHOB6iTtY3aVtjPwtV7hjVAzpvqCuh7TI6qhi7I0CXAlIJA8k0HpBmydoosegi9VDLA2BkZHUDs0CSRG47gge228SZ1SmbcRVfLqlFsRDYbxsY1pw/t84qGe+MzcmIlQrGdURqIS07RGdluYYoB02mDjAajfHFAdbt4VbT6pDhwEjLjuiC6wBCZOEZ90Rc32AgFR+qG27LCr/52v6Rl+exEHVtEJiOaqKAdwlSx9rZU+zd2CXERFo0VCHSVpFBavCqxhcNFYJUQqYmKMwWmZUKLAzxxRxWVmhvXedLl3dZzhdszxb8xU88xgiBWHgLWo9Z0ZamM7Z39rDxCpGOldGIn3j2aawakqxBh0OWLgzaOR4Co5FA07Jczumy4xsbDGYzBsFpli2eEvNQs25LIolAJIoizYLRqVVkcUA3d37k6RPq/UpO1F6ez5VqiGpidmuHmI22cUIluMFyntirB5wJgayOGXzzxgLykuGw4pHVMRqrshSiadEu0TUd50dGqmo+8egWQcpq1UYVq2rqdkldB7QKPPrQOiRn1gVCNAKKaGm55JYRioSK3HVEiYXNEZToSm4WeHIaFWx9DfZaRt2CJRVZKrogaNcS3WF/m9092N2d8chjm0densdCVEKkc8cDRG/oOiV5wrPSTodos2SUlGEdmAyG2GJGl5Sb+3Neu36brZUpl85PIUbovDzSWdVYt0Q0cHZzlZqA1oHYL6wKBwtCmJWWKIK2hndgGlirFJdI48rW1oT97Yb5waLM5lcRdWPeJior685DFdBU1iznnKj353jqSBrLouJkVG2HuLDrTjc39vYbxlWikhO67KKzzEHrjKrAbpuYLVtOr0yQ4Ay7RD0eYW1LLRnfPwCJNE0LbcdH3reJSEVuIJghLsRhKM8I6ZBJbEmdYVKWaUhaIgzQyRhPRpeczowwCgyo8CqS3QldZhSF2a0dRAPD8YhZ0zHMDdkzX7t2j+15y6c/+CjBwJuMk4h1jVTKQVaqnKnSktYjGoSQO2IIVNGZnh5zu4lsz5sjL89jEdJ0yYnBmDdzUs7cmS+4Ol/ShoxEx7pEzg4ZRIcFalUp48mIu7OOL716h2SpYJVSC11XKCxagUbQQDKnbZZkiXRizJuWvdZI5tTmxEVDBkY4tZc1Lzl1WIKsjrYLJmpUbgiBRyY1tr/EFktIDUZbVg3kBM2SyfnTxOmIVE+RDJGOrMIKTqiGxFqZjAdUJ5X5cGN2QLvsyO4MakPdef31G6xfOk+9OoCuQUXIRNrckXOZQdndm9EuhUunhlSV0roTQiCY0bYdtRoEJQRlpImuVfYODiBWZTlEJUhOdLFiWCkhQE6ZzqDGSaKIOi4DiE4tLTk5Vc6cWh3xgx/7AG1Khd4SlDYlavMCvbp6nTZllgKD4ZCcAxITXddSVQF1ZY0OHQ+PvDyPhajr9YBlDrQ0dMnoluCeubW3y6gWRjghxrJssGtRlFANOLtZcWa9o1ZB4givK8LyABxqAXKHekXODTFGvK4ZSlmtVomX5YyhJlSF8kLqV85ELUv9xctqumZOFkiqBOnJP16eS3I1Qk6IgomiFeRkWBVBhVURsO4tmFahBmTcM6jTtSd0gdTKqGZlNMB9TJcbNsaJ7cmYrm3Z32sJg7LIKChUdUS9ZGTqGAiDiOVUuA2tF/ycJRyBWGOW0CqSktNpZDgYI2qodYW6U1dIrAmpgRiJFsndAVR1WQidjYOkmLVMayVXI7J4mTTIS4REDoFFmxjFHnwZFOm8xl+gAAAJFElEQVQyFUISw7PhVUXdJYixrHJ3yoJpOfox9ViIGocVKZWV4UOvqMaB1dUhuZuDOCOteiYhPWiyhgA2iEjX0HlNHcrYpAZCRcaIClkDIkr2Fs2ZGMElFkJo22BNiyYlawGDtG1b+IZdRupI1TmTCDKYIG2LpAaooJtxkGqwyESdUV1YSm3OBAmoZQixrIg3KWvVqxptW6ihTTXSzU8ucDLnVKCMGghRMcC9Y1hFOg8kLdBYyYmD1qljxzTUBSqahUo6XCI6rZGdgwLbEMWthBEuToXhqiQzgnfkwZAwmuDNkqQJFYUGEMWqKWqJ0JTx3YPgnXF3mTjAmaoy0ch8seT63T1cnMfPThmFIXUV0L4yqQjRa9COZWNYlak8QNOidYXngLwHvuqx8H69K8gcNyeLU0UtdE4ZEoJTaQQJNARay7Sph5l1LQU6GMojKwlyNhrPPY2sp55Z7ilnjkihkRUsq/R4vFAWHrtRq1FZQnIu1JeeaOapOGgvX2u4Oe/oJBHEGVTGol3QpA4js+igbY2M9uNnh7lTSWaQQDXRoCxNyYMhhKOPU4+FqKaGhqqwkKWiyRnLUgic1kNprMVywbQuc0OrEbce9CEBCUZuM3sJcorQFZwOISIaUFE0RCQOCKMVJIEvlyggXUNdxZJyTBlJDZUXTI5JKPfRJdbEOcWc69euIcMpnQQGdeT86hrTUOGiuFIYERmSG6knuJk7mQ4zIVaROs0IiyWpOXo61rHofpVIlozjJAFCoEoCKgTLaDISGUwLaynU4CWuPMTGVclBMqNBhXrvKInjVjB2kFARkkFepsKOMEAyKVYkF9QgoLilwl9SwJyEEOtSMS6d22BntsB3dpmIMJ1O0KhEg+BtgY4EwT0VhG0vNFIVlJ13eJtL+/dcsmBHbMdCVA8OSei8o5UhUyBIoaaAIpIRi4QIVRgTYuErBS2/TQp/QUIkagaLaDBIASeRNRA8Yp7J6oQ+keHqND4o6Jxly0ACHgqX4SBBCMqQRLSMO+QM45UpK+MxSsItFwxdcDJO8tiD7aSk8HNGQ6Gjimp5NFQL30klkBD8PVj2dixExQVXxxlBLGAcbTosQDApYQCFUziK5SFuTZAxQg8HLbDe3I+FpUt2gYVFTAJjyZCElEuLFSmQ6NragmztaSrkwmqqgiK5RbK/BajtyARxJCq+LNhZCxm8osWIZngMYFaI2xIw7RG3ORUgdTXFuzmkQm86sRylYE72TFRjmCPqHWB4clotWJ2oxfsdeAsWewdDga5AnkNX6Nnex4rmuDpRq+IQZUeCE1tFBsOCKkwtEiKqAZVcAJfZUIyahPconkKXLHllmo6khRVZeQFwtdlpcsJjVViJZEIffzkBTYZbB1LRSkfwiLIAlGwndOot5wakJrijXUsW77m8BdZMMlyKM+UyQroFGgcFm94WolghjQXcS/ZGnEL37iG8hwg5CYfgyD9gC5NzT0RTRAvLsO1xhxH6xcRKFKED3EvYQkqlWzYjatmJoxZIVvjC7gmL5TknFAIJbzOeneTlERyRE+oolQyagymESCSRyeUpAyKdU57cE0MVQjUgjgOY0uW2OENSvGU3QQKFzmmZ6JnsDh4Lp1/oN0gpoMnibTne07/LcFv4+W6pkL7dC7U7BKqezx+8OFtNhr1mySAII6nIEt8ihxdOIWVOrh+XY1BcO5q+lR89bP2YiCpS9eNQwdDkt6DOJaGOA6qla/RMlkxqCsseCm9Qq4hXTp63PfwqkqUjSKByxSSRreRurUuIOhJGoIlsLVAyVmX/Ge27ayFnCr2s4L3ptCBkXXI/5accLIw2poJWz0J4C2opBePlFJ64g2GICNEDFuk986O1YyEqPXZOKBsHEAoZ1HKpzWWcAiT3bECjnS8Q9QKmwnEr8WTBbntBwbriJW8IORfIhjuEMgGf6WjNcSJq1jtPDmYEEdDy92xSenG0sHpNyKKYO0kcC7BsYGWQQGIPaS44W9oS7wYtXMSuE8a1EERoupb8HoCUjoWoqmX2wkvkXmJM+m5MBKfs5WJ94UrPq9fQ069zSVK45dKiHKBGNRegshllU4lEViV4V7hHqSroVxLikSCZFCrUy4PWufAoC2RbBLe2pBMJfe/REoMzChWd5t4BL71AoOyGkXK/OZJqSR2ScALZUwE8vwf5n+MhqghJc7+LVo+PU4eQe3+mQJmDgHjZSCgFAyuCYOGtrUeC9FNgdGWbEUtlQwMtpG6lELcxRUOhfWfpoZVZIVZYLfjcChZ2NMRDTe4yYoJ1imhbKqAV8Pc4OgtqqlhR1YGUizdfQrUeFdvfjyLk7MghbvakxqnJ+9YpwuG2WWqHIUvq0c2CUzJF2RUyZAE73E9NC3pVPBUkq0PUDiwUpyuEsgdFNiwH0JJpClKe9MsC7oaltgwFXkhsCSF4YRlqFsSa/l4pSQ7PDCOoZoZDRUPAUstbm2sIZXcrz1SxJiUr0EsUz22/w8fR2rEQVSopzPxsZTxNjknqv3BVGL+56RMKEaQrJdZDIsuuFyWMscPUD1rmVqVQWLMfbitStiExL2xhpy7E2JwLOq8fYytJ5XmnrqHUoD7B70LOZROk1gsAOgQYVgoeyCljFsh0vBWBqlF5hQYnhIgdsvYxkh198uFYJPRLDFIAxxwCk3PfUj1RVK0Qz4XaLQWQ7FJmWOgZvWXO1fuEQsT6LtJcCP2WJhlIoiTxnoxNiXNFSYUxWjY7ghLfJsNzmdpzIKmDBjJSvGSBoEZQI+WMdQWIWfXBingsXOBsdJ2ROytOm5U9d4wTmnwwhy4ncEVdy0YIsd+MLwSwgIQydhaMXC5OhhuEAjs3K3vGSCzvcyrd6aGzVbY0yYUZjKMuhe9LIAt0Alb1rPtkWC4b8WUPeBCMOXa4sQJ/MF+rBLJVmCtOVyqCJ0wUSwGLjniF2BKWhoZAPoxb5T3Z7OJ44AEe2NHa8eh+H9iR2gNRT6A9EPUE2gNRT6A9EPUE2gNRT6A9EPUE2gNRT6A9EPUE2gNRT6A9EPUE2gNRT6A9EPUE2gNRT6A9EPUE2gNRT6A9EPUE2gNRT6A9EPUE2gNRT6A9EPUE2gNRT6A9EPUE2v8P/u5UzqPofGQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_model(model_ft)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们用可以固定住前面层的参数，只训练最后一层\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_conv = torchvision.models.resnet18(pretrained=True)\n",
    "for param in model_conv.parameters():\n",
    "    param.requires_grad = False\n",
    "\n",
    "# 新加的层默认requires_grad=True \n",
    "num_ftrs = model_conv.fc.in_features\n",
    "model_conv.fc = nn.Linear(num_ftrs, 2)\n",
    "\n",
    "model_conv = model_conv.to(device)\n",
    "\n",
    "criterion = nn.CrossEntropyLoss()\n",
    "\n",
    "# 值训练最后一个全连接层。\n",
    "optimizer_conv = optim.SGD(model_conv.fc.parameters(), lr=0.001, momentum=0.9)\n",
    " \n",
    "exp_lr_scheduler = lr_scheduler.StepLR(optimizer_conv, step_size=7, gamma=0.1)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "训练和评估\n",
    "\n",
    "^^^^^^^^^^^^^^^^^^\n",
    "\n",
    "这比之前要快将近一倍，因为反向计算梯度只需要计算最后一层。但是前向计算的时间是一样的。\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0/24\n",
      "----------\n",
      "train Loss: 0.5602 Acc: 0.6967\n",
      "val Loss: 0.4210 Acc: 0.8105\n",
      "\n",
      "Epoch 1/24\n",
      "----------\n",
      "train Loss: 0.4979 Acc: 0.7418\n",
      "val Loss: 0.2921 Acc: 0.8824\n",
      "\n",
      "Epoch 2/24\n",
      "----------\n",
      "train Loss: 0.5891 Acc: 0.7254\n",
      "val Loss: 0.2140 Acc: 0.9281\n",
      "\n",
      "Epoch 3/24\n",
      "----------\n",
      "train Loss: 0.4340 Acc: 0.7869\n",
      "val Loss: 0.2246 Acc: 0.9216\n",
      "\n",
      "Epoch 4/24\n",
      "----------\n",
      "train Loss: 0.3768 Acc: 0.8443\n",
      "val Loss: 0.2333 Acc: 0.9150\n",
      "\n",
      "Epoch 5/24\n",
      "----------\n",
      "train Loss: 0.7258 Acc: 0.6885\n",
      "val Loss: 0.2524 Acc: 0.9150\n",
      "\n",
      "Epoch 6/24\n",
      "----------\n",
      "train Loss: 0.5147 Acc: 0.8156\n",
      "val Loss: 0.2195 Acc: 0.9412\n",
      "\n",
      "Epoch 7/24\n",
      "----------\n",
      "train Loss: 0.3560 Acc: 0.8443\n",
      "val Loss: 0.2075 Acc: 0.9346\n",
      "\n",
      "Epoch 8/24\n",
      "----------\n",
      "train Loss: 0.3713 Acc: 0.8361\n",
      "val Loss: 0.1981 Acc: 0.9542\n",
      "\n",
      "Epoch 9/24\n",
      "----------\n",
      "train Loss: 0.2797 Acc: 0.8689\n",
      "val Loss: 0.2184 Acc: 0.9150\n",
      "\n",
      "Epoch 10/24\n",
      "----------\n",
      "train Loss: 0.4125 Acc: 0.8238\n",
      "val Loss: 0.1972 Acc: 0.9412\n",
      "\n",
      "Epoch 11/24\n",
      "----------\n",
      "train Loss: 0.3408 Acc: 0.8525\n",
      "val Loss: 0.1965 Acc: 0.9477\n",
      "\n",
      "Epoch 12/24\n",
      "----------\n",
      "train Loss: 0.3618 Acc: 0.8443\n",
      "val Loss: 0.2258 Acc: 0.9281\n",
      "\n",
      "Epoch 13/24\n",
      "----------\n",
      "train Loss: 0.4089 Acc: 0.8361\n",
      "val Loss: 0.2272 Acc: 0.9216\n",
      "\n",
      "Epoch 14/24\n",
      "----------\n",
      "train Loss: 0.2555 Acc: 0.8770\n",
      "val Loss: 0.2488 Acc: 0.9020\n",
      "\n",
      "Epoch 15/24\n",
      "----------\n",
      "train Loss: 0.3573 Acc: 0.8484\n",
      "val Loss: 0.2141 Acc: 0.9346\n",
      "\n",
      "Epoch 16/24\n",
      "----------\n",
      "train Loss: 0.3498 Acc: 0.8566\n",
      "val Loss: 0.1986 Acc: 0.9281\n",
      "\n",
      "Epoch 17/24\n",
      "----------\n",
      "train Loss: 0.3628 Acc: 0.8115\n",
      "val Loss: 0.1983 Acc: 0.9477\n",
      "\n",
      "Epoch 18/24\n",
      "----------\n",
      "train Loss: 0.3209 Acc: 0.8770\n",
      "val Loss: 0.1999 Acc: 0.9412\n",
      "\n",
      "Epoch 19/24\n",
      "----------\n",
      "train Loss: 0.2523 Acc: 0.9098\n",
      "val Loss: 0.2567 Acc: 0.9150\n",
      "\n",
      "Epoch 20/24\n",
      "----------\n",
      "train Loss: 0.3754 Acc: 0.8238\n",
      "val Loss: 0.2081 Acc: 0.9412\n",
      "\n",
      "Epoch 21/24\n",
      "----------\n",
      "train Loss: 0.3556 Acc: 0.8361\n",
      "val Loss: 0.1883 Acc: 0.9608\n",
      "\n",
      "Epoch 22/24\n",
      "----------\n",
      "train Loss: 0.3132 Acc: 0.8484\n",
      "val Loss: 0.2036 Acc: 0.9346\n",
      "\n",
      "Epoch 23/24\n",
      "----------\n",
      "train Loss: 0.3974 Acc: 0.8156\n",
      "val Loss: 0.1934 Acc: 0.9412\n",
      "\n",
      "Epoch 24/24\n",
      "----------\n",
      "train Loss: 0.3379 Acc: 0.8443\n",
      "val Loss: 0.2170 Acc: 0.9346\n",
      "\n",
      "Training complete in 0m 44s\n",
      "Best val Acc: 0.960784\n"
     ]
    }
   ],
   "source": [
    "model_conv = train_model(model_conv, criterion, optimizer_conv,\n",
    "                         exp_lr_scheduler, num_epochs=25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ln02jwxRLg+TyRdJ+DiUtjIYkSUiiCE9obtxRYv7kQZLyU1z7gufS6FYZG9mMTDSWFNhKcW5ukXf+0n/kJS+9ilpVkC5tY3hogNLQALfceC0vunkHzWqNk6dO88jBh6jXW1TX1ui2mti2i+v5uE6KsNvh4EP386IX3sr2CY/Nk1s4fvooyhiqlRUeO3KIo08c5fBXDpLEAavLS3hOiieOPLZuct0Q5H4Npkeo6HmhAsBILGnj+y6pjMvQ4CDDgwMMj44wMLCJfG6QdDqP6/r9bhwmRjbzvCtuQOT2EzViXvMzf85b3/5uNCN8+csHmV7soPxN7N1eIGm3OPLVE9wwHrK6+AQP3/sYOzdtYcuOPRz+6jHu/PiDNFo1PHqjSp6t8FyLRrOGVArbdTFS4qRzuMYjl3aptkPKzYBiqUSQGAZGNqEwzM0tc+zJo7znXX/Opi3b+NSnP8XJo8fXTZobglwlJILe6wNCIGXf5gqJsgQohePnSGcK+Kkivmfh2C6ZVArPz+P5WSzloZQi5ztsGh5h19Y9HHnkXgavezUfe9+7eO6BUcZHFdKVlBenqC8vsrTURrgRyFE+9bjD97z6B+jEDm1nG7V6BSEsNpWy7Lj8Jo6dOE671aS8ssLy8hJCKYqlIq7jkMtmsUjwCyWq3Qg3lycJOzzy0CGmlyq0tOL6m29h//69zK8sMzaxhd/59bczODjI5q1b102uG8JbFtKgeNrJlZj+K5Dsd9MChVIC4jyWn8WmjY4jhBT4XoZUJ4frphGizHC2xPTpo1y5eZLVICZfrXLzLdfwibvuotyY4+brryZbGiRVKFDKj/LeP72DrZOb+dxn7sJLZehGgrvu+CQ3XTtAtd5kdMsVNJeWaXW6aJ2QzxU4eeYEg0PjCKxeSNL1WAoDLCck7wnWyifJDY4wKXM88vBXmDo/y9J0itLmbThC8cThR/FTGe675wvsuWz3usl1Y5D7dNgRUMICq/8qJCykZVDCRkoX17LQUZNmdZGwtUpUz+ONjJNOl8hlhmjUlqh1GoyWxjhTzXDd897E8ROHiO2YajdEpzbzxfsfwZAwMT7Aj77lV+iokK8cPkIm59No1PCzWV7y/a8kqpyg3uqyUotZmT+CUi5Lywt85CN3MTA6QhjHtLpdJsZGWVlZZdP4Zkr5IvmBAWZnqixUqlRXWoRByOaJzXh2xNrMEsObNjM9PcNavcJ1193Ayvz5dZPrhuiWpXKwLAvHtrEcG9u2sW0H23WwbQ/bcbEsF8vLkskPk83mIWrRqM5D1CBlKfKFIWzbZ8/eW1itBaSKIzSqJ8hPXM1nPvtpyvWEpamn6HRDbrnt+czNVjl6+DFqtTX8tE+hmEcLTcorsXC+TNipUyoMsjA1w+GvnuOaPTtZLZcBm8F8kVq9zsLcPKWBUc5NnyGbTfHCl72G2VMPUS0/RWWtwmK9ynNvv57dk9u5ev9WiqUUM+dn0UZTLKVod1sI3f2W8vlOsSE013WsZ6I8yJ7XrFRvReXT3rNSFhaQsiW20nQaq9TWpjn71Q4BIZv3HcAOD9BcnqK80qLVafHlLxxk6846Y6NjdOp1VoIQNzPE5z55D7e/5HkcefQeNg8XuOW513H0bJXB+grt6izzp7L428oMju/BFyGDQyWeXIiZOn6UvVfYHDsWcNsLXsTY2AiPHLwP3/OorK7RatVJ1CDKX2ZzeicD+TV0u8WOXTs5evIUrWaVwkCJ2ZlZLLuI42Xou43rgg1BrrKc3quQkCSi92pkK9VzroTsvSIphS0lCgupO2QzOdr1Ck7Gx9M+2VSes40WDx1+CuIW9370Ezx+9DjoLLe++Dk8+sghPM9ieWmFlKd4+IH7yOdGeNWrfohENVg8/yjZfJFuc4bV6iKvuurF2I4PZoal+QVWVu5h364xqpUy1qBNeXkZz3ZYmJ8HISkNFHjgS5/FAMXSVu65/xA2MVEnYnB0mOOHv0raMSwvLdOJY4JmjYce+By7d+1dN7luiG5Z2TaO7aAcG9/zSHkeju3hOX4/GtT7OI6PclK42RECWWRkZBNxY56ku8r0449w/Mh9NGp1/OI4W7bv4MCVe1hamWVlpcJKvUO3C5aVYIyhXu2wvDzFoUfuxnMdXv2alxHFmkxxGJ2s0Vg6zO5dI2zbUqJU2AyR4fCJeWZnF4nCLvff+3nue+A+fM/nyJHDfOmeT3N+6jQYwYkTX+XW22+n3Oywa+9eFtea7N1cIgxCdBSQJJrEgC0tZheW102uG0JzHdvGeib0aCFEfyRHKVAWlgQprZ4WS42yHbL5ASrzK4RhFS1tnNFd1Juaaitk9dg5wuQ8jq2wnDSf+dhHcD2L0sRW2idO4/opoqhGEkvOnF8i/dCXGNm5h3TWo1kD7Sia1VXasc+2faM89vh5LCuFcDsszlcYHpgnXciThF2W5svIRHPyxDFEktBsd5mdb3J24e8RJFTqbTJZjesbAm3R6AZs2jzMyvwyZcuhWAzWTa4bQnMdx8V2fFwn3ZtC46VwvRSW55Fye2E+13FxPBfHS+OkMuw9cDOTe66jFTosrjRZmp1itgJjkzfwhrf8FLVqG+MVWVtdxctlcB2bztoaXsrCyA5RYIiChPJig8MnTuN0q5jUJpQUGBTf//rXUV8p89B9x0EKcvkxdJzhtW/+T5ybWaS+tsahh+/n0Ue/hC00M6ePE0QhYWzYvWcPy/OL+K7PVTfdwIte/BJGtt9AhGa06HD7y36Mq6/aTzad4tqrD6ybXDcEucp2sC2n5zTZNsruecye7SAdG2VbWLaFYztI5SAdn24iODN3jq3b9pAYwVLgYkybcycP88XPHyLshjTqZToxZPKDmCTozaR0FGEnJAE0GreQJgg1QnZZfOpBPEchhaI0NoGXySPCFlEY0G52sLXijve+i1YroNNu4jqShYVZlAShXJqtDtJ1SRdy/Op/+zFatVWS5dNU2gFrzRpXTI4gBNz97t9hea1Oo90i7kbrJtcNQa5tuziW3QvG2w6u7WB5Do7t4SgX2/ZQlotQPdKlVBSLY1x+zYu46wtfIvGHeerwA6ScLNJKkSmWyBQG+PE3vBnbSbNw7hS+JxjIACZE2Q6WBUliqJcb1NcafPrThykWMgghsKTmPX98J/NHHmetJkBYCOGRGx4knc5hRIq1SpNNm8cZyKUojgxR74QslsscP3maj37oC7z3b9+PP7SJE4urnJ9bQIqYa/YO89M/+5+JAHSbfMbmoUcOrptcN4TNtZWFpaz+Op5e2FEIG5RECYlUT48YSZSUqP4o0tDoVq5+6Q9x8CN3sFiu0GgENFsBsX6ATrfCZz//KVaWFjGFPFIKfEezeUuJelVgyQarq22y+RTZlEs2n2F4fJTKQptQGzrBKg+fg+tv3sa9987geS5WAnEUgnQYGPRZnDtPJjvM3XfdwZatOwhCQ7tbx3IUlqO4alPAQ2dmKI5OcuzxhzklFSfuOEQYQ7UWkoQBuYHsusl1Q2iua9so10Yoq9ft2r2ghmtZWJaFUhausnH6Xbcx0A0Dao02N23fwvbJHSRxh9HhQSxbcNWuHdg4nD15glTaZ9ve3Sgnx+JSmfGxSZaWy4zs2M0tz7mFd/7J/+IHf/z1vPKNP0OrnRC5mltfcA1nFy3GN03QaTaBFmHYJEkiPCuFY1k0IpvxTcOUV5ZRtku7XWdhYZZqeYVi3mdpDT5wzyK+LXnknk9RK4csVxSdGGIM9WYbpOQHXvGKdZPrhlh8/eSxx0wvxCifecftbffiylIIjCUB0ZvKiuD01AnK5RrLc0f56N0fIDYejz72OFt37GHm1GkiJN1uAlrjOhCGCfmsQ7OdkC3lyfoJys3iqgTpZnEQpAcGcT3B/PnztBp1onZMPjvIzFwdJR2UpXAch3RujFhP91YeYnN2dgbfVlRq3d5UWRLW1jpUmwkp30HZFq1mm/iC6VLFrE2hkOX1P/Qafv133r0ukYyNobnKxbEtHMvCsa3+2K6Fkj0bK6TEot8lK4lGUygN4tuSykqLdGGEE089iZGSU8dOoHVM3I2ItWD3FXvJDQ+RzWUYGCqxfbyEl3Mp1xX1WptGVxI0I5ZWK6zMLfLkY8fpdi0OXPN8/tPP/SpnpudpdCtU6gvU6iu0OjXKlXNcvmc7k6OjVKtl0o6FQGGpGAEkCXTbCTaArRDKJtYGLQHZmzKk44hWvckHP/qxdZPrhiBXJ12kslBWb8qolArZt7XPzKWy+tNvlKLTDahW6mzbvYdTp57kkYcPc9vzX4QVCXbu3E4ql0abhHza4fiRJ+nU6ihb4aZLuKVxzj+1wO4rb6BabTM3vcj07CyLSzWOn5piZa1Npxvw+GOP84f/+4/ROsHEIKVg31W30mxVqdbLnDp1mienKjSaTWzbIyFhIF8ijAMazTaWI3seeTcgajWQUoDuzeKUUmBZimuuvZrLd31baZy/I2wIcu/8P3+OJSUaEPRDjpbCCIVRAmHZSGUhpEQKRTZXYHRkhJPHnmDfFbvx3IR777kXN+Ny/vwUcSixpU2n2sSSkB4YQhFSr1WYmVkkn/M5fegLZFKSlK8QWuNaimsOXMGrv/cF7N63jQceOcjf3f1BnvOi5zEwkCHleZx74n66saaQSWNZPjdfv41Kuc3C4iKWgtVqDZ2I3lqkBBwLgliTxBqtwZKQ9Jaf0W4lHD58hCNPPLluct0Q5D557ARz8zMYbYhJ0Eb3VhaInufcG9Pt9WlxGNKsV6lVFnni0CM8+OVH2bx1O9mMQoZtBkoZSkWHbFZx3Ytv5MA1e0ipGKUE9WqFVnWVKE4wuOggZmggz+hIhoFiiijqcPuLXsnZUyfwvTQ7dlzGrsntDJRKpB2NdDPYjiKVS7Nj2wD3fvExdu7eycDgFubOrxJHCUlsMEbjehZCKhINsQaNIda9ceuU6yCVotEKKS/X1k2uG4LclNvkT//oHawsnibqNukEHaIoxJgEKS2EoL9QDIzWKGVTWVtl/1XXcMNNNxF2OkSRwmQGqNZDps5XKG7ZwZEHv8LMzAx+yueFL3sZQdcwMJAjiSUog7QUa9UKQZhgOTbtdpOz56bRkeSRgw9w+vQJWrUWjmVjG5CmieU4CBNy4nSZ0+dXOHHsDEtz59i6dYxiPotAkMlkcH0LP91bUqLl05PeIe0JYpPQTRI6QUJpoPRNZfPPwYYg93te8AKajRq/+3u/g9YJQdAiTAKiKCJJkt4ccNmzxW4qTS6f5/qbns911z+H+dlplOXguA5JEHLbC24CpagvLrJ9cgu1mgZsPvHhz3HD818JUuFnJSkvS2mwgKdcrr3xRgZLJTKZNI8feZxOp8PHP/whvvCFL3B+aoqg3UJYFvVGb0J8Kp9leNxlYLiAJiGzaRPdTsjSapVM2kEK0LGi0egykPHxXRcH8CywHAVSYYCU49LphOsm1w1B7q2v+CmymYRudYEPvv/dmCigXivT6NQIOk1MED6z7EIKARLOTp3l0Ucf5PCTxzl58gQ333YD4+N5Dj3yGCQJtWqV+YUZLJmwsNTC9hyW56Zotpu8/FU/AmGbxtoqpSEH2V6h3a3T7bSYPTtFNwj56B138Nd/8kdMnzzGWnkZbdnc9ek7cVAszi6zd/8t1MtVJvftJuwKKo2IbjvBz2YojWSpttoUMx6rzTZhFON7inxaUMz7tNohloZcIUNpcP3WDG0Icn0/xTve9k5QgocePMjc/BmSJKDbqtHstmh0W4RhSJxEvRZrGB0ZxXYdXv7SV6E8w3AxhyUdtMkgLYk3Mka9npArDVBfmaPa6HL2+JPYwMfe/15QIemUTxTZ2P4mut0O1eoaK6srhLFidGKMqFWn3WySRJqUl+U//rv/CsowOjLCwS9/DoHFyvIay1Pn+Zn/52fYsn2ctWqHQibP3p2jxNogLYHoP5hCg5YKDQwMllhbqzI111w3uW6IIMba8pyRIqZdK/PGH38tQrn87794D51uiLI9lFA4Xr4/MuRjKYsgCMjk07zpx36QL977EDffMMmW/Vfx/vd8gDiIuPrGq/nqVx7HSIVrSb7v9T/M5+76MJffchNPPvwwRmhcN8ZSJdYqq7iey1ojIFcq4vs+CwsLTIzmaddrVJsLkQaFAAARh0lEQVQJQRBjOy779+xiobxI0GqAVsRRSBSEvTlYzRDPs7EdiyQO8VI+84sNpNb4aR8XqCch3W6CKyVCg5cSrDSiizeIgRK9YH46y57teaQledv/+1Zyvg8kRGGXZn2FRrNOp9MiCDqA5uTJJ5Fa8po3/BBrq2Xu/Mu/Zef2TYRRwjU3XE++mEeHPafs5KFH8LMpFmamCDoB3/OKW0kCmF+tcdvzX4KyFeMTo0hiamtVRgaGeNn3vZ7X/fibyZYKXHH1AYrFAcq1FTwlsWyFUgnK97Fdm04YEieGINAoIdBakrQTbCmIgW6rQzcOSKdstm3KY0lBodCzz+uFDUGurRQSie+m+JV3/A23HSgxM7XIz/3CL5LzU6A0tcYqK0vnqa4uUq1W6HQ7pJ0cL/6hn+SWKydYLDd56ff9IEurNfL5LB/7wN0kzQ7FUoZ8IQVJxOXXXoMJEvxSlg/efQ+7r9jH2FCWT3/6c8wuVVgpL2FZimIxy9zCImdOHqOx1mL35GUcf/IkE9tGePWPvJF6o4KrXCzLQsQd2t2IHVuHKGRTZLIOxiR4tqTWTYiVQiPJZxSlnMN4wSLjBriWAaNR8h+ucPxuYUOQK5WDpudFpnI5fvqX/5xczmF1ZRFp2/heCoWh1alSqSyzVlsh6LawUhaffM+v8MG/upMbb7iag48+zEAxQyNMWF6u0gxCwrBDKiVZKS+yeOYY7bBGEIJy0tz+yh9htbzK9slN5KVNqxlSq1dRUpDOOBx84gmeePIxTNzCzyri1ip3vPtduHaGbtBBa0O9GTM4WGBxsc7IWIlOu8Peffuot7rESQxRgkSzY5Mhl0oYG9QM5mDvZIFt4yBdd/3kum41/xMglMK2bCzlYZHBcfP81i/9BClf88OveR3ZdJZcIY/vuZQrM1RWzlNZXeDs9Bluu/75jO25ls99/mHy+TQjW/fhEXDF/l3Ytk1xYBOVygrFYp6pmUWmzlaoLlbQOubeD/0dQRQzc2YKEyf4toOONdW1Klt3HyDvK5bnZpiZnuINb/k5VubWgDaQEAaaej2glFGMlmzSOY9yucJAMc+hQ4cxWAzkU4wPOGQd6EaCa/cIhkqaobxkYrjL/m2beMnV65eHakOQC71UCUZJbEdiKY+Ja17PgW02juryF//rF0mlMmTTedKpDEHQZK1W4fMffB8f+exn+PxHP0RusIBKDCvnD7Fl8xAzs6dAdSmvLFEa3IpQLtJOSKUV0oIXv/yl3P/wo0RdQSJdjOfgZTJoA57vsHTuSQayWWxLkR+b4GN/9U4s36HT1XS7AUpptk4U2b5tgPJaSC6XR2tNs9shCA3awHKlxuREhvEhh7xt8DMuSmgGCzG5lGHneEApv37zljcMuUIKLClBWihbkXZS/Pc/+DxjmZBPfPazfP7uv6RYGmFsaILBwVHWqudYrTU4Nz/HZVfuRnfqTJ89QbPZYm2tTjo7Rjbrkx7Ic+7sFOdnZxkZ3Mxlu4bI532OH3yMXeOjvPW3f41c1sHxYKiU4TnXXk19rUo2l2F2bpZGo0J96Sw///M/T6ve7OW80IIoMtRrbV74wufSDkPOnJ5lrdomDhI2FVy2DycMFX3KXYdSPmH7do1Ng2t3KnZNpNg1EdMN21x7xdC6yVS97W1vW7fKv11EUfdtsr+cREoJopfHRiiXUe8Yzbbg0MN/z0hesn3vc3A9l9/8pf/BlvEhcgPj/OBrvo+pqWlq9TU63V48d2C4RNSNCYMGhUKWar3D4nKVwdIWvFSByV3b6bZq/P3HP0Mn6DBQcOl0m7SDgMzAKJ1aDcuCPbsmqaxW+OSnPs+ePXupry0TG0Mr0DTbMadOTdHpxNx4+y0UrSoFVxMBL7xhJ/PlMgsrbSqVmJuvhHbTYctYzIlzLju2OuzasZt65zxXPe+X/8d6yHVDTLOBr2V0S7TGUhaiP9x3y+v+gtGdv8+pR+5lOLWAmy3SWqpz4LLNPPT4Ed74pn+HUDETW8bZe/kt3Pm+97Jjzw5yGUGrmVBI58A46KhNyoLK9CkWO5qF2afIpFKAg+uG2I5L0AkRGOL2CmHYoNvVPLR0grQrGco5DO29kuXyIvFaHSETTJRQrjTZOepjz95PWkq2bYeT0wkPH32Kel2RFgluWhF1FY4xzC0YrrmiSL0zx0CywPax/LrJdEN0yzrRKL72l1xxEqPp5X00MmH7lW+BzAiV+iIf/rs/5aPveQd2Os3s7CJXXXc9juewf99lLEw/we7LJpg7c47ve9kbKK+2e7mZuw22bN/Elskxdtx4E65jsJBYLrz6B16BEoo4SXjOba+kWq3SbncJI40jFKUsFLIu2XyJs48+yMu/95V0Qw1xQqxg65DHgW0BQ0VDt5swX9bERnD7VYqsFzM0ahgcMrz8dW+hlB+h2RQ8dnQFHVqcO1vj6InKusl1Q0So2s01g+x1xZYU0E8pIBIwSpDEAUHQJgzb/PtXH2DPlS/kwx/+HIaYT97zJaanjnHooYc5v1ThkYfuo9H18WXIK171cv78z/4aZQmGxsZZXaoQtAO8lIel2zgpnzgSbNmxh5NHHyclFdpOiGIYHR8mblVZWY3pJJrtW0ZB2kxPzdPtxgxlXaqNmJddrcmlDNLSJALqHUWhBLlcgeZaG9kMkJZFqZTQaMLuW36AuSfupmQrygEoO+HXP3ARR6h0L/cfpt85a63RiSbBYHRvcJtEIrD5n3/wJ5x+7HNkSg5/8M4/wUhFFMa04hZ7d+xg28RWuq3zGFHhzvf9H265/XmkBwaIoyaDgw47JofJZcGyoNUIabfbnHzicW544a20jcJzfPxUBplIOiHk8jZZz8c4A1RWq3R1PwmaCwd2aq5//vNwsgLf7/U7u7YoVGwYLBbwHYc9O2DPZMxQFibG4NTDdzM5IpGpkMmrXk+1un5y3RCaW6uWjVLqmVCcbVm9hBj0prMKExMEIVEUI6TCcRSW7L0frizN8NUn7uPgQ1+m2+mSyW/m2FNPsHB2gR0H9lOvBXz6Ex8jl3NwbIugE+FZFm46j4pbNNsRrTYIKUl7hpVKh2wmgxBgu7C60sSyJSQW7ThGa9g86HLj9oDRAYFWBqk0xbzN0dOaYlHhxRKDZtdmgysj6pEkZWmSEJyUpBsUWVqsMjBk0+pofu2D3YtXcxVJL32q0UgJWsegY9AaYTRCWEjVmxxnKYGSFkiIdYy0LIqlUbK5HALBqaP3s2diiFoi+NCHPs7n//5jeH4vvGkpm+3bthAYRdJtUmsFdDoJ+YEc9SCi0QjJpB20CHG9BBMnOI6DALpxiCU12wqa2y8LGdl9GcuBSzqncWyFkQk7tyt2TowxkukyUYxJ4oR0BhwjGMxBowWViiC99fvJZcHYXZYqybrJdUN4y3GUIG0g6WVfVVL2UijQS/snpe7tU5Ik0URRCMSEYS/7muM4pNMpOo5LrjDI6vJ5bt2fZcAZRfppqs2A2elpGpWQPdssFi1FebVDLgOOZ1Eq2syejwgscD2HTphgZUu0WitYNrSCXoLRbWOKK3fuwxKnGTLHSI+mWFq1GfIUC7MJ0gWnNUspDVt23MTywqOUFxKCAKpOHi/dxFMStfRevBTMLCk2jV3kEarERCRJQEIERCQ6uCCxdi8/ougvwtYmJko6hFGIJsa2LQYHRtm+YxfDowMUPZtOK6Q0diUH9m2iU1nG02u8+LZrETLkKw+fphu02TxRQglFEBhOHV9gYKhErlAg0QnptGRxfoFmK6TdCdGJZO/+LdyyD2x9kmYY8vBRi2qzgyMijJswXFAMqxjdAcsyrM4+SCELh0+CqyDjN7E1rLUiuqHG0mDZCTPL66e5G4JcbWK01iRJL8O5NgZNSJIExDpE6xijexldpTDoRGOM6S87EbhOGpKEqFXDsTVSCszaNI21NSwRUcp4HDx0BB1LQiPpNDX1ZpPJfdspFQsYYdFt1LBMF9f3kSZh6+RWOjH4QvGSKzVXluaI4xjfESgl+J7nKMYKMDGi2FVKSBnNYN5i87Ak6lrUuzA9G1PVLvccgsVVQyWyObogmV9TfPGEJomh01g/n2dDkAs8k2NZ8zVvOU4STJKQ6BiI0LL3lJv+9FB4+r8QDOlMgeGxTQwPFMimXVa7IZWqJuspjpxYoV4LUCpCGk0SJ3S6HY48fp7FpQqFnIvlKvLFLEEnwgiL6afOM17wKaSgvNpLXuaiQEO9JllZDVExjKShE2nyqZCglWDnt9BuGbRRhB3B5Vc+h8lJyXxZcOZ8SDGlaEZQzDooIwnURb7Kr7dMxAFtQSTQxiJODAbdI9poojgmieL+tFeBVKqXEtBSuL7P+PgONm25jLnVOlHcwfdtGkHIYq3D4GAB3/GwhIOWBt+3UdrH6JhEG6r1NkE3YW62RqINM0sdjGuTd0Ou2W+Y3AHNto/nCSbG4IU3akaGFWN5Q9CEtLKZnnOwPJg6N8W+V/8iU4sGBETlvyeXTrCsXhrfZk1TyicsrSkeOAmzyxd5Yk+Di6afC9CyeDpHutH0s5sn6DhBJzG6/+cEvZX4CqVstEmQlsPA8AQveMFLGRkdxzE2AkkuVSRJDMNjeby0QxILpLQZ3zpKGEWYpHduYgz1bshaswMShuwQS0I3sFicUVy9N6ETSpYWoFVPMM2EJIRUykYQsXlbTDqV0GjDYx/9HTypOXraUGtramuac8uGgbzPlk2G6QVFREjaVUTWxT6eKyQKiRAKSW8CmaG3/kYLw9f+hAaMftpGKZRykNLCdTOkMwW8fBHhZkmlikRJwtjYBF3jkvd9FperhMZhctc4nm9Tr9YYyDukHUWr1cFOwJM2A67N5aM+lSbkCw5ZV7Fvd8LQYMyN199AMZcwklXEGpbWNO1mRHlVISJAKfL5XijGTznsOrAPESvapChmNI4KObMsaAYuQ3nDQq3I1NRFPrUVIJESQ2+FgU0vNwbSwTK9/8BLEk2ik749TtA6Qmv9TCoj1/ewtCJfHCLRkpVKlanzs+zYspWRTRMIEtJeQsaGjBdSyLu0Ixff0Vy1b4jrrrH4Dz/3ZnSSUK13uHpSsFwOMKZDt5Gwuggzxx/GQ7G6ZCjXhki5Cts1pPMJ7Y6gugprdc3RaVgLQpprx0ksOLcYUA8Vh0/C+K4riW0HheLKK4fJDlzk/3FgTC8htZK9xV+9xZq9uLJIBOh+KNJoDL1gRxj0/r9A9B8KpRyslE+4nGB5Lpm0z64dO1mtLKN1RDGluOrAfsrLc4yN7ODoiVOM5GH3JpdQr4KCez/yZ2RdQRApZlYTPK/ARKlBNzLkC4qgq2k1FK4Hl03uYvr4CqEN7VASqJ5HvFhWZNzeMtTTMwnGTpAKwkShnZgH7jvO2fmILRN5ZhaPI436VuL5jrEhNPfp/MpK9TQXJRG2RCEwQiL7a2N7lGuSJCYxEWHYJYi6oDUGi3QqTSqdozg4SBhqQlPBUiGdTpMDl+/DVTGW3cAWs0yOJQwP5jl9rk3QhKxXQGkoFGDXJFiJZEu6TSeERlVz+qRmZQEKRUWrETN96kECY4iEYG5VEyQJfkaTKcLgWMj0ckI7MtQ6ilRhF1NLsNLKMV8BSKjUQqRyCNdRvzYEubJPam/Rl40tXZTsLcbuxZh7T3cvTtRLQR9HXZK4S9BtEYYtdBIhlcPw0CYmxrfjOoa0SlFrBmzbOs7mcQuXp9i5PSGdCpk9C6q5wutuVdx6peby5/80hRSMb99GYy3BEVCvw/S8ZPuEZHzUxpLQWu1wy3UWrdDQjqBdei1DRYVv2eRTipyvqNYViU4Y36xoNBVfeOQMza7Nn33w43Tamob2qLYSgiCh212/VEUbYuDgEtYHG0JzL2F9cIncixiXyL2IcYncixiXyL2IcYncixiXyL2IcYncixiXyL2IcYncixiXyL2IcYncixiXyL2IcYncixiXyL2IcYncixiXyL2IcYncixiXyL2IcYncixiXyL2IcYncixiXyL2I8X8Be2A/HE1jmWkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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drGFz2z/ficLGb7nUSxG22UXcGsdLQmLh02xJLC1Nys6S+NNAhOf7NAOfPfvGaTWnGR5MSFSOMJZEsUeu2EFnn8Xk8AHqZRe/VyFUmjBsYhgmlq3B7I0nJaRSORy7k3JUp8YAflgjCueO13khrnQleBrrt1zJxNDTbNh8EdNjHlOTJeLuNgaH7qFRb0K5imnHiHgho0dniL0KVjpDHGdZ3nYJByZ+hoojJib2IK1uLr3kWn7+8P0cPfooUuikWIyhp0mlBFGgEbOQIBgkIaEat8jZiiiMQVek0yZKU1SrEeWyzvCwTasWoBIBwubCS66mv6sHz21xoLCHkaGnyNptqCRBJWBZFlJAEPkoEhwtjQhsklggohQm7ZSaIX5rTl5OAfNE3DiCKExwWxMEns/Q4UEuedklfPMb9zI0PkBEN6msT9CqEAUNStND5PJL+ejHP0OlNYhqtnHbzbdBUOesF2zgqcefpKNYZPu9DzEydhBNChQ+QqthmS2iKCTRbBIZoRuglE4USlpNj66ijRe0COMYNwhI5VI0a3VE4iMIOP2cF7Codz2h7zM+MUXHgm6ue/EbmBz1GRs/TGn6cWI84kSCphGGPlKTNN0GKcskCGLCKEIlkiBIiKJTfLS8afO53H/fgwwNHkUzHKx8lv/9vz5ElHiIOEZ5FQKZwrI7SPQKui5wtBkOHXmGw0+Ps//IPfQt7+A9b/0X/uav/pgFSzaysPtcUsv6eNGyt/LTu/6J5215NUGQ8NjeuxgZ3oYQZaSU6JaFUgpLT5Mok1bLx7ZBsw10ITBMn1D5FGVIUWiUSvvZuvVKdj2+i4GDD3LxqquII52+FQU2bupk3zM97Nj1HXSjSZx4BFEVFSsyqW6cdJq2QpFSuUmpWkPJAKmd4uKKRCeJFQODA7S1LWAiewilfJI4JtteQGoNvKCG1CR2th/bLOD7kjt/cB8iqFN1K0zPHCH7vTbCyGbvU3sYzfoUrDzDO5ahZdI8PXqYRXY3S7s2EyRlauU9IGIcx0STBlFoo6KYhusiDRPLFHT35tA1Hc9N4zZrjIyOoRsp3MkK7UWD8VSK9uJp2FqG0khA5CSUxsZoNuooJzoxE6UShBTYVpZmw6MWjhEEAUniYRog5G+zSOJ3w7wQt1ybQmoJSdhgfPwo1dY0ES4JitA30MwUwo1Az+KkA2bGj6OTw50KWbdlFdFQlZmZER7e9jXSqQKh38RLRhGdeVw5zkuuuphP3/gBnsl1cP0b3sbKrWfw+OMNRoZHyeXz5DN9mHoXoa+Q0sDWJW3tGknURDMdNp92HhMTVZrRA4wMHGWospuO7gU879IXE1SHePjIAPuf3kfIcTSjip1KENggBE52MVIaEKVQSuD7Ln7QxA9KJHhI/RQX9/jIGJoOmoRMMYtpawS2TdAMaJbHkUaMpoeQCKpllyBOsFM5NHSkbJAtmJQrimVd66kER7GsLqQh0NpDXnLpO5kafooNZ6/k4ssuYvFCh2arwNBwF57v0dvbRy7bS0rrJvQtZJQmDEMcu0ajlhDX2zh6eARTt9i6/gUcznfTV+ikq6uPlKWxZMMiPvbnf8yN//h57vvxAwwNlAj9BjO1ATTdIm5aaKZDKCFRArDxwxauFxG6TaR2ir/EaPojaKZPMZ2l5Wq0WiZIB2EJnLyi2SihSEh8nSjWSTmCmbHdaJrDE9uOEyctNBS1lqJa9jE0m0YjxcyMouztI5c9jbfd8M8cPfQjIr8BYcCyFUuRZp6+rk7Sdg5UDt81cKsureaJQRDCZnJiiONPP4wXxFzxwss5Z8t5CCSfv/GjBGGd3gWnkSQJ17/ireRyec44/SxQEpXoEOmoQJCEEqOQJ6xHJImFJtrpybeTMceYKO2ZM17nxXxuOqUh9ATdUMQEBG6EJXWy6RRKQEIKTcshEMikhd8MEFYKZIRmxGi6RgKMje1CJQYJNlYqTbUa8f2v3clIeZwdjx+nPNWiVvNoNAIMYdGRL1KdatBqBIRBhC4DNCtCtyNiFbCwp5+p8ggzpRKRH7Jj73aa1T5WblhHV9ti/upzn+Gyy6/k+rd8nIydQcQx7b3djI2MIcw8XX1buPIN1/KyG16JiE0sM0/aaSOv5UhpGVKiSDH9u6wz++0wL2puy8uSSA2h1ehf6OCk22k0YkYHhzD1gHw2D62FCFMQWUNEUUQoHFIpBxU0SBXyTEzOEJMQxTXS+W6UCyqukEQN7v/+TZia5PzL1nP4YIQX1AGo1WIiV+F5Fh3tJqapoZsx7kxEoxbxzPhOhkeOYNgOxTaH05ZfweTgAUa7e2kMHuP9b72WF299BSte38uGM9djpCXVyRrLly6hOVOjeqTEXTfexdIz17OwZymTY3WMlEXNrUOiEEhMLT1nvM4LcYkhiTRCpVFxa9Rnhmk2FL7bAKnI24tw3SYiZWFYGpFfw5Qp8kWHvq51jE5PkQ18vIZLKp1DalPEVhY9ybJ+Uz97dh1EUaUyXWG6Vsf1p0lijVo9QsQ2Slnopk6xYBP6Ec0gZteuEUwtoWvBcqrTo1QqFQb2PElnbgG7RYsh7RkMw2TH0Z+T/0U3S1b1c+jRY+wbepCRmd380fs+wM77n+Clb7uBwT2CvnUd+Go/2+/ZRnd/gSgJIYmJk1N8QBXUPDAtquUMbYVV9C1fxtihvRSdfhxnCdPDQ1iJYvHKNQh1Kfl8jsBv0mq6nHfxRr77/X/ECbM4KYnXrBM1amy9cDPv+9B7SWkJr7niD1FKsGPXY2TabYQMcRsBjYZHsdiGkWlAZZhQ78CQFgFlNp3xGjJWB/X6JIeS+zl99QXMjM3w4uvO5C/f81YSBJ7nMTV9iGxXjcuvvIbvlL7L/rFRTFNn+8MP0ta3gg//1ReJVJrPXfFOXnbGGpK4i3xhikcf+Dl+7BJEtTnjdV6IqxA0S3VCt04zSNN9ejt9F7ycmYlxZkbGSAubF7ztjxjYM4ApTS5/3XoGDrVBFFMbLpHSF1AK95PNpGhVGhiGxujQYd7/h+/B1peghE3gnvhmaWpkGqRCJYpUOkM2r5N2EqRo4rkBgaZjpdpokwVWre3n+JCgOtNGaaZM73KTW/76JoQTYUcStxEQR/DD2+7lts9+n/6lG2lUS/hBTOdymzA4gqlZWFGLo7ta/Pi2B1l77gaO7C6BHuI2S/hBac54nRcDKiUUYegjELzqza/gzPM2oicBk8dHkFqTrjVtjO1/HMOo4EXjjE069PalKBZTYCn0RkJac6iN19GwqdWajByrUJmWuG4D25JkCw7ZQhG0E4ttdctESgMhFb4bEHk6vmcxPRUwNjzC7sHP8a1bPotXgg9++F0s6kxx9JlBGgyAqdPR1U46n0XKRbzumvcQZwwmWvu47HXncPkbzkboTdBbbHieYsm6iHvu/lu09H6mJ3ZT9Q8i9AQhA/ywMWe8zouaK7QUmmiidJ1i70KGj48weDSgs+tsvNYegqhBxZ2kUW4xMThCbapEV/dppLMpglaJ17/7Kr73JZu9kw8SUQalQOiIIMPUMZ8rr7qanTsfoNQaBykQiULTJELGNOshSunYKQOkRRwY+G4ZKzWNvqrEgb0mX/zoCO/55JVs+9E+jh5fyqXXb+LNr/p9LLtI2Kry4GN3Y+geji0RhkQqHdfzUFEKt+7jpNoQVg5Tz6Fpily+g2o1xnGK1FvOnPE6L8QNgzRmWmLaOl+8+ZvkMgvo693I+udvZfvPjvDM3u2EYQ3TTJOmj4GRp5isPobUBNWxMQzrHYQNDVNPk8QBRqpFrTrMhrUvJmOkeOLhbbzqbTfwg9t/TKU+jjA1TOPfih54Om7FIagavOD8y0j8NWw+fSH7DzxGZ2E9P/vB7Rw9tpQbP/8OIhXz9e+GGFYCQmfVhiUcPfxLNM3inDU30Js3ODr8BDNTMYnvY2lt2KkijtVOEqewjAyJUsRBDEJRrv6qbTn+azAvxO1a0CQOAl7wovOp17IMHhumNHM/93/nKSrNUTRTR6ZsROLR1t3JdPU4i1f2cXTvPiI74ifbPodb90gbOSzHwHJSmGaOYwcexQ+qeF6LO78dEJudSMNBlyFSKExbkHbaSEKL2E3ztne+i47+HjZsgT+6+E6ufe9LeOBH2zByNru270TFIXrKxErbBCH4Xp2jh45ipxbSbi6mZ6XDzEjI+HDpxKtMNKRtEPsJsZZgGQIpJXEYkMTRiQmFTHbOeJ0X4kq9TsqWDB7fQ7NioOsJQU6RTReY2FMDkVBsz2EaCUoMk0xUOLKrSYCLbUfUPReh+wRGROIbFAoFWrUAmKHYu4D+wlq2bLwEx5Q8akQMjDwB0iOXT+NoRdzQo7NjLZ09PQzsa3DLJ+6j1NjDFz57DNvqYPD4Xn784CPEcQXqGiIxWLJ8E1OeiyZN/vhPvsAvbnuE8mCRex/5PJ//ws389Sf/Es0wIYYwCGjRREtr+AEIIfBDD9/38Vx/znidF8tJLrnoapW4dUzLpL3zTEaP7wCZxjRyhC2HauMYUdAil8+SKBNd2CRBERWO0LaonSCcRjM8Wg2X8ZEamiGx7AwYGZ539pXs3zVO3+I1dKQNdh+8h5nacVLphHwhiy16SHxJPrsMFWh4WoGN67dy5MgeqtVhNp2+hvWb+rjly59n784HsawMy/tPZ+jYHlZs6OPIMyMsym7CzDoEjYi6tYt16y4nm8ozOvE06VQBy3TwfB3LyiOlQEiHRr1MvT5JozXIXdu+cuqu8mtVY1qNgMULzmV6bDu6WWR8uEKrOsG6zZezav1aHnrgdsLIpVmpouKQlteiraOPC7dcyRdv/xRRNINp5TFyvRAOU6mUWbkiy47HfsAZay+jXDvEvU8+TMbRsDQd3wto1EPMTEze6UaXBgs3b6K3ewMrVmeZmjnMwOBR9h9W+FKwvnsr9d4m0/U9DJd28+HP/ZAd946xvEvjie0fJo48rn/HX/BPX/4IOx/9EblMLxu2bmZyagwvbhEEIdXmKEkiiAKd2G8BPtEcPufOi0ehtGGStGJKkylazTS1cplIxRi2TucCDSEWc+YZL6FRb+IHZUIVoNs61eooB48OUSi0IYWN7ycYMiCXy+A4MRMTZcqlGY4N7MGtT6FJ0HUDFSckfkiz2sTzPaKwQTbXSUe+i0qpwUMPPs3g6CiaNFm0eBV6GYYm6sSxxLLB0CJu+Zt3s+ORO2lblEHP9eGFDj+99Qjnn/NXnL31Q/QvWcaZm16Ow3o8z8cLa9Rbo1Rqx6g3h2mEFdywSqKCOeN1XtRc148BRcQuqhMBSEG+ezHZzh68co5m7SAuVVQgKfZkEVEaI+Xi+wl7Dt+Fpop0tPUzNjlE0KrSqkT0LFqHRkicjam7x5msBsSJhxI6ihApdaIkoVyb5nVv/zjfv/VBqtWdxErDn4h578evYfvje/nh175Dz5LTuPiCM/jqHQeIW2tJ/BmCtM/Hbn4nzYbJ3T/KUXfLjJr7GP3xLrrW9mDJPHd+6dssWXsF6/ou5tjUQxw6/m3iwMNzq6hEksk4pLLmnPE6L2ruzESZRGUJPDANBy3Josk0M8NNRo/uYnrkIP2LVrLAXsA1r3wT7/+zD3Pu6dfS09VHW3sOZER9fIzIb6FJnSiIEHEa34UgDvCjkDgOkVpCFEcoqaGZBpohiOIWB3dP8r8/9UqKHWtImiaFzjw3/6+bka6Fkdco5l1u+duPsHR5DstI8OIax45s4xPvfzN2QUFUxc6b6Ibi3KvPp7stz/6dw4xND/Doz27ih7e9j+N7d7Jx0xLCsI5hg24qTEvN6Sq/eTGgWlE4XSksip1dBGGEYxYwsjn0SMcKYPni9azaeBH5TptlG3sg0cgUYGLM5aMffAPFzjSDAwcI4hZhqLBSBTLZIpXxAd70rj/hh9+6HaESIhUQJTEpO4PjGMRJjG0LEmWy1H4/51zWS8+SpYzu9ulZVOHWT/4jf3TT9VSm6nzgA28mETEKE6USehZlmJk5RnvnUkaOjRIrQbe2jnPOeRX3/+xGVm+5iupoE9fagxZPc+kVF3G8MokuBvHDfo4fHkKTKTQj4ns/uevUHVAZdo4kjmg2K8Rxk3Qmyxuu+xB3/NPfkO3IsnHLatpWdOC7OtOTCr9RpXtJniXLIPEFAAAU9UlEQVTLTS6+/NV89/bPopkZIt9D6tBsTaFpOomhuPOr3+TTX/gaH3jvDQR+EykFigApTaTUSIjQzBr14q1M169l7OEqj93zKLpq0r00g5kSfO5jn8S0DFpeSKxaxHHM8FCDBf2LmRwtoxkWGiFl9nHfLz9F4ghMbTfnvuSlLOhv5+nHl3PTzW+ic8lCpitTqPhprn/FeobGGgSBNWe8zg9xzR6EqRO70wRRlcmxvdz3g88TRXWmJiZYuO5q7vrmzQwOHKbeaBElCbXmML3dyzHTeWQ+R8pJU29Nk0rr5FJZkqBJ1kwRyyr3/eghbvnCN3n7W15JLJvomk6sYixHw8ooUilFtrCboer7SaVj1l1jsmLBB5nY12LnQzsIjAk0F/KZNMKQtFxJy2swNVpBxQoMhYg1VCJZvGwjGX0hketw2x2fYsnCV3J05IOsXLuGfUf2o5smrfoMF1+8jhde+Qle96qr54zXeSGu5RggDWR6OXJGoYuAtFHgzLNWsefJh7nzO3ey+8DDREFMq6bItRVx8g7lYIqwPoYipjRVxk7b2A6092SYHivT3dvFsv4r2PnUNp56ehd9C06j3DhIrCJS2QQnA0IGpPMJmXyMZSk0UyGFzx1f/zQjA3UWd68klS3Q8hOk5tNo+YhEx9ADdNNAYGCn8sSRR6Pm8vTe7Uhl8uKtb8Z1GwRBnd9/7Q+48+fXYJsmtVqVfDFDte4zceQbbDl73ZzxOi/Ebe+IGRsZRDVsNEOjr28t+e4uNmw5g1Rbhh/e+c8o2cQPEoRIEdULXPXq9/Ddez/EilVdTE1UQRekszaDh8ewDZu07aCJkPGpnxHKhE7rYjraHHw1CJpBZ0+MbiZouiSdBd0Aw4xRRJQmE8plH7fpcnToCClrLTadLFm7mqLjsO/IfZSqhxEyoTZVI4pigsBDaDZmShDGHlHHfUSpkK7FNl/99g289k1bePChx/G9Iroe87VvPcRtP/glmeQU/0CuVp4hVk2kHlFvRBwecEnl2jl4xzZO37IFzYypVVsIwNBSCKPO0MA0tlrEzGQOtxHTaA5Dd0w26zA5PsqSZWvZuvE1PPCTR7FUO8tfeDqOkzCZbCGVb5HNN/G8aQxjGtOIQXogEhLl0t5psXojHNHyzIwHNN1d1ImZ2P4wKSeNTGJiGROGPrrdicDkxRe+gmwh4u4f3c6Cnk727TtIq1rm/m3/QDqXYtcegyQOqNbK5PMF6vWIqckR1izomjNe58WjUK05imaGOLkYKx2jZJ2me4hsh4m0LZxMgSiJQINENfCDANNysDPdpJ0Mhuyhs6OdRYtXEycFFi5eil/zcIMKuaxFIMd55tBuErOLM5dfy6LsRbRbZ9CR2YplrSKODZJYI04SMulOioVlnLnxhVz+kivYsOlMbDtN2slDDF6zSa69gIo0LDODoSlcr8lPf/Z1Dh1+iJZ3gEZ9L2NTFZRMyOXzVEoz3HPPNiKlE0UwPVVClxEvvOACAlGYM17nhbhO1sFtergtn7aeND19RSJqtIIp9uz6JcWePkzDIUFHWgXQFfuG7iYMPd543evZsmUNa9YuZWHbZjTP5YXn/QF/94WbKJc8su1drDptM23dOZy0xaL+LjrTqzG1RUiVAz+NivIkSpJ2ekjbPdhmO5Ojksq4ie8q0ukMXrOGrukIpRg9NoFXbyK8ECOKMEWTti6Xg3ue4YpLXsuFW5fQnk9jG5JEBBDHpNIZBo4dY91pG1jYtYA1p53O+KiJ6fTOGa/zolnOFHTCuAeZSOIoYvGSxfR2b2ZifC+Veh235ZLryNCo1SGu4xQyTE4+zR++7U/4x7/6U6ZmqnSe1kXByOHW6ngNyec/cR9uqBiZmMG0q2TNgGb1ETJWgUKhne4+g1ZsEIaCJDZoa+/H0MAPEir1Kr/cNkm1IklkjThsUehqJwl9mrUYzUkThhLdtHDdgC2bX8Dk2BRYwzz5+B6kcwDXrbKkv8CBwRmUhPO2LqGzo4uBoxVqtYgdvyjjOAbZQuo3E/Q7Yl6Iu3L5Yn4xNk4cRdhFm+Mj49RmDlCammFqfAiSgET65LIGnu/TqLeIgoCbb/oEWqLhOz4iLBC4NRJN8tP7v0Ay0+DKN76b/Yf3Ec/UaJkzBK06q5auQ1GnNBOB4SJIEFJSnpCkrV6yhXZsC6S1h2bzCKYdE/gRzdY0IpYsWtiLH3g0WxFJGPPCF1/JL+69h/MuehM7n7iNUEtwa91knTRxXGPJglV0dfZikKNeEQjVQJcShETTDRI1d43nvGiWa6XFZFIuHV2KbC5FyjKJAw93uo4UAUIL6erJIQ1BHAZ4/gxS0xEC3LgJesz01Ah+2KQZ+VTqU4hchh0P38s73/124rhCxT3M8PTjjJSfYqS0nWrwNA1/iFhVsCydwLOpTKZoHOsnVd/AGYvPYUHPShq1Oi23ya1fuo+f3P04etJJ4qVI4gTLsXjsiYfwjIDte+6gZ3UnmYKJk86QRJ0k0Wks6FxK1skC4sQqhDiFJkxAYNkZDC0zZ7zOi5prxd1EUYgtTerTDYIw4JzVr+eS5/fyldv/nDCpIqTCMECpiN5FOWozNklikU9BkPjgh3giRjMgJjixU1xlmNu++hmCuIZKQqKwwfDYk3T2tBHqOnZaYdkuWpQCTVH3pknKIW4zIgp0ZKzQNQ0lJB/44Fux7IhKJcSLG0SBT7qjjWq9ycq1Z1OeHkYmFppUWJaNEAFxrFOrRMSRTspJARpxbKPrJgkJ6WyGSM3d0vp5Ia6p66hYx5EdrF57FTPTIxTbNZpuhZ7iQjzlMD0zQiYPnT0FoqiKnYEkiZHCoujkGJ+oMlI7iCZMsoUsK1csZnRsgLHJw8SxixSShIjKTIl6o8zSle0sLGQxUyZho5vIt1jctZbaaMjowX3IXETgedhWiqgVkiiH6cohIgGZnM1MuYPhYY8tm0/nyV3bkJqFI3vJ9uqISkIcGcRxBLFEC9sRrTSKAEN0o+kJmh3St6gPK3OKbzJWb5RJYjBkFwQ+QbPEwOg2Ort66OjuYOh448Tqe1fg5IrE/iQBaToWJODHmKqTwKugWxoqklRKDfa0BujqNYmiCIQgAXQpiVSIUDqNhkKqDLWJbuJGO8vXrqBgpCmFx6j4LfSZEm7ikcQ2qxafT8urkbPXMl7fSZxOE4YuSMVYdZK3vOVudKPM8MyXGZkYIgygXksIwxDTMogRqCQmjGOEJkll27GdBklSobtr+ZzxOi/E3XfspyAFTsGhVBqi1qgwNrCfXJeDoWu0ogYiTlCBji4EvtDJmBHNqkejEpJEDXr7LarVFtm8xdRIgB+MommbEEwg5Yl/cxMCJDoL+jeyfvHltGeydK9YDVGIlUtoVqY5PH6E4SNPoWdiQs2nq9gJWo3I90hn2zG0AjMj05gpjZbbYnjE5+/+6SL+5M+3klJN0i0Tz3fRjZCkEUMcEvlNXOkRRB5tC1J0dBfp7O0mUT7puety54e4YdRAt9LoqRaVmRLNYBJFwPRYkzBOyOZsFAlCU2iahYgkbhBg5wJAoURCEDboaO8FS9C/vMDMeJVadQihKXQ0VKyhayamrdPfew5Llq0DTColl6QmWba5h6lGlagVIFNQ7Cxy2WWvIQkDvnfb7ay9YBNHDgyQTi8k9Gug/nWXHcUlV65D4aOIEVqC1BRCU5i2jq6DkAlKCKSWkMmaODmLTMbAtnMgTvHNtBEKpSKKXSVK4y2CxEWztBMzLn5EkkQodWJlQhJlCIOYRIQkcYKu65hWk2qljN9czMLlKdyGz1nnvJAdOx5A007swKpJjbb2XkxpYpjQ2dFF3Q/QcjXu/da3ePLhHJsuuJjX/94NHN77GJ1dC9EE3Hzr20mAQ0/Auee9nO/88EZsR8M0bVau7+eci4oYWhE/qGIaOqYZYugxtpUi9hWJCtBshaYEQmhoToLjhNiZLLZtkSStOaN1XoibKIEKFYmYAUuBKdGEjogEiQJBhBDgeTFj4+PopkAKnfGhFgsXdTEzXSefW0arrJHXlxGIQZ7e8zBCgCZtksTAsFLomkOiYg4eeBhZX4gWCzafu5YXvfkVPPTtn3Ng+y9Ztvl07nvwNryghJ216VncjdcMCMUYd/30RpT0sJ0Olq1aTPtCi3b9TdzyqVt41wev42j5ATQRI2WA1ARC09ESSRDUkUoQiwRQKE3HMEMMkznd8GRePOfGSYKSBoVOHSevoVsWlpnDsNJksm1EcYhCxwsgjKvU6wGNeg2lYGZ6Gt9NqE43kfhsOfcS3nLdn+HYaWzHRtcNhDBQiYnUTTQjw8su/kve+r6LGDtcorjMYvvnj/Om97wV0Wbw8wfuwvOq2G0moR4xNRaSzrXTaLYIYh9d6iilkbUX8+g9R/jk3/wxvtrP3j2K8sgLibwcidKIAwlKRwqJVJCoCE2EGLZGvs2goztPrmihG3PH67wQN4wT0CUP/8TGkJ10dLZhalk0abB29WaEhCjUEBg0m3UQikSBFBK3VQcECRpK8ykPH+Sn994FnKgRQgikLjGchFCroqVg+94v8+C9u3jrxy8nnWRYconJjgfuoZCvIQKNM87diq8sdCvP71//UQYPj2GaKSw7g5Uy8Ro+D/7sbqrVKh0d/ehiIdu2HeDSl55DEluEnk4QgopiECcolhJ0S6M6U6deb+H7LooY3TrFv8RIYoFbKzPSqjNwIKLY3UNHpoN8tptWvYVpriayJZrho5sjeJ6LIkApDVSMNHScnEG9NMkd3/0cb7/hJtZ2JyxeYVBcvII//fDfYzg2+fYmS9uupTWuMzzaoj59nLVnLWDtWWczeHAbE+NjVGeOU/VblGam6LL6GRud5OxzrmbXjjtQZoJuCtqL3bRqVYIggrCLFZuKXH7x6xgZmqJRrzA+1MJtRigVIzUTQ4DQEjRDkMQh46PTWCmf3t4eMvn8nPE6L8QVwkSTATHg5DPUS9MUc1lqtYAoTuM3DYLmDMXeFM16E03qSGnQbDbJ5XrRzSZJrNAtm7ZChq/c/mf0p5u0HjSYalboX74GN6oRhNAcLVKZHue0TVsYPzTBHR//Cp0rerjiugt5ZPtd1Ks1UkWbjOPwxte/gy/8/V9y/mVvIpPPUehKU55p4NYNepc8H3fS57TNZ7Fk0VlcdnWRj/3powRxkyj0SRJFEisC4ZFIgURhoqMZGokKCXyJ67rYtj13vM6Hrx9X9m9RqVSMppkoIYlDAWIRmibRAknsVnC6QJiSYjGgPFOlUQoJw4A4tmjvaKNRL2GlJJo06WorsLr3So6M72G68kusDESigTAlF6/5HhvPXcnG80L+8LybeOMH38Q9X76XVEHj9HN6+Pq//B2apXHN77+dz970cfQkIbJc0jmTpudy+uZLOXrgMKlClkY5QDcEsVanvVggn3eI9RaDAwO4zQCV6Agh0IVC0wVOXqfYa+KkDRYv66Cnu0Am73DtNR85df+dJN9m4uQkVjrGTFlIo0gcRfiNOrrh07d8I7a+lN4FFmHSondhGsNUBEGMYZnUq3WWLOll5er1XHnhR9mw8o+YrIdESRUlbVquRxTGhH7Effvezvj4fnb/TOP9n3kvldpB3vyR86l5e7nte3+HRxMVC75866e54GXnYBR0IKbh+URJhKKKU0xoXyDoWGQx0zxO0y3jx010U574JittoBkgZIxQyewfcyQkiUIpkJqJZRlIKYmiuftfoXnRLPstH2Xr+IEJWhumLpBZg5defh1xY5Cndu+m5TfwRgqkMx20amMnVgY6JoFfoa3YxsYzX0xvxyLCekCzUaU09TRRVEYqiR8pdJmgSY0gGODWu66mLbuGDvkaisVeHvjxd7n8tc/nR98dY8CbRs/lSMImOx/bQ6zH+LGPLdK87Mob+N53voDSNNCXc+jgMLppkM6lWbmmm7Y2m4mSQbNuU636CE0Sx8H/ae9uWuuo4gCMP2fmzPudO8nNTdK8NZdEK4pScSVUcWcRpYJaRdCdojvBjd/AlTvBheCuiBVBspEupWK1tk0sgkUJ1TSYm3vz2tz3mTnnuMhnCIRhfl/hYc7858A5g7AEYBj2R6RDGzOmsGRGbgYwOrmV81Q8uSZdQisHxza4do8oUkh7j19/+o4s7dFu3sOx73P5zfPstnq0thvYYpy5uQmqYz7DwRGBJ3hsqcHZxTqL83XO1KfwwgAhBDoXGANKaUBiWwlz9cvMLoQ4QZtHz9f5ffUu7b0Ngtin3d5Aug67u006hw8J4oj33v2QtVu/IX2XuFZl/e91pGOIqiEzs3XCMCROalRrEzj+8QSstQZhEEIAGiyNyjXG5OTZAEyOLQt+Ja/lGurTEteTQMrS8hg6d5iZTli5ukKv30G4I5JEQLaJdDepjCVsNf9iojZFdW6Cr698z8oPt3n79bfwPJ/J2XFEVOPh+ha5yiAzWIDjucxWX8JXMcIxpOE2ST3HS1Me92YZDvbZ+NNGWAmuf4RSmm63y+dffUFYCcmEj+4rKnEVISJ8O6TZHDLdOIvZ8tjfS+l1IEs1RhlsAUIanMAmih0qiUcUyeML1XQfR57cWaFTEdf3NhgNodcZ8eqlS3z8yQf8898f2FbEyjc3EcCgr1g+V+WN9w3ffrmPPMpRfY07b4GwiWOf0VGL8ekdjDYsVVwO7oxQJsOybLAUliXQORx1d0miFocHe4jKLyRmjExpvEoPNxxDBj26nUO8imDU10hAuprBIMWWPo4rCf0qo44BVeWpZy7y8gsv4rou7eYuq3eus7N9BaMGx7tktsHzIIgEcRLgusfvcdsS5Krg/zj49LOPuH/vLjMLMbfWBhx0dsDSOCwdDyImJ3QmuXbtX7abFaQcsrezB0qjol2mGg1ee+cC8zNnObfUYDjqc+P6z2gxIlea2niAHUb00wFoTSdbo5Vu4nsDpquGNNPkapLGmYvc+HEVkxu6nR2yYQcpbRYfWebBgxau6yKEIfRqOFnIcxdeoRLN8eTzCzzx9DhpJqjEEd30WW7evkqm+khbYEsLL3AI4oCw4hCGCtd1QCiMObntx1PxKVQ6GadioCqdjDJugZVxC6yMW2Bl3AIr4xZYGbfAyrgFVsYtsDJugZVxC6yMW2Bl3AIr4xZYGbfAyrgFVsYtsDJugZVxC6yMW2Bl3AIr4xZYGbfA/gcZQUIB+wMPqwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualize_model(model_conv)\n",
    "\n",
    "plt.ioff()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "py3.6-env",
   "language": "python",
   "name": "py3.6-env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
